Title

Author

Date of Award

Spring 5-2016

Embargo Period

4-12-2017

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Mechanical Engineering

Advisor(s)

C. Fred Higgs, III

Second Advisor

Philip R. LeDuc

Abstract

Many developed nations depend on oil for the production of gasoline, diesel, and natural gas. Meanwhile, oil shortages progress and bottlenecks in oil productions continue to materialize. These and other factors result in an energy crisis, which cause detrimental social and economic effects. Because of the impending energy crisis, various potential energy sources have developed including solar, wind, hydroelectric, nuclear, and biomass. Within the biomass sector for renewable energy sources, algae-based biofuels have become one of the most exciting, new feedstocks. Of the potential plant biofuel feedstocks, microalgae is attractive in comparison to other crops because it is versatile and doesn’t pose a threat to food sources. Despite its many advantages, the process to convert the microalgae into a biofuel is very complex and inefficient. All steps within the algae to biofuel production line must be optimized for microalgal biofuel to be sustainable. The production of biofuels from algae begins with selecting and cultivating an algae strain and giving it all the necessities to grow. The algae is then harvested and processed for specific uses. It is the harvesting or lysing step, which includes the extraction of the algal lipids, which is the biggest hindrance of algae being used as a cost effective energy source. The lysing step within the microalgal biofuel processing is of particular interest and will be the focus of this work. This work discusses the optimization of the biofuel production from microalgae biomass through computational and experimental approaches. With atomic force microscopy (AFM), a key mechanical property that would aid in the computational modeling of mechanical lysis in the in-house computational fluid dynamics (CFD) code, Particle-Surface Analysis Code (P-STAC), was determined. In P-STAC, various flow patterns were modeled that would most effectively lyse microalgal cells based on the shear stresses placed on the cells, which will be compared against microfluidic experiments using lipid specific dyes. These results would be influential in developing an energy-efficient method of processing microalgae for biofuel.